Digital Methods for App Analysis: Mapping App Ecologies in the Google Play Store

Team Members

Keywords

Introduction

App stores play a key role in determining how users find and download applications for their devices. Rather than being neutral conduits for apps, these stores are owned by companies, which are driven by logics shaped by their branding, customer-base, and profit motives. This organizing and ordering creates an app ecology space by which certain apps become connected and presented in particular ways. App stores host a diverse range of apps, from popular social networking platforms to everyday tools, dating apps, and apps targeting niche audiences. A multitude of third-party apps also exist to optimize, repurpose, or appropriate the functions of mainstream apps. In light of this, our project seeks to understand the app ecology space produced by app stores.

In order to investigate this, we have chosen to focus on a case study examining the app ecology of popular religions. By identifying the top apps for each religious and building networks of the similar apps recommended by the Google Play Store, we have been able to highlight how these app are organized and presented to users who may potentially search for them in the store. This research draws on a combination of digital research methods, producing a new App Store Scraper tool for similar research. Findings from our case study indicate that the religious app ecology is organized not only by religion but also by the suite of tools available to support individuals in practicing a particular religion.

Literature

Research Question

The overarching questions providing the foundation for this research include:

How do app stores organize the app ecology space?

How do they allow users to engage with that space?

What kinds of ecology types occur? Do certain ecologies repeat?For the case study of the religious app ecology, we have refined our research question to examine the technicity of religion by asking:

How are religious apps organised and connected across the Google Play Store?

Methodology

Digital methods development - Semi-manual technique

In order to develop a method for interrogating an app stores technicity, we began with a (mostly) manual approach to data collection and analysis. Since the Apple app store has limited web features and a locked-down API, we have chosen to focus on the Google Play store. Google Play provides a list of apps that are similar to each app. To examine connections between apps, we decided to identify which apps Google Play deems to be similar to each other for the top apps for each religion and to identify how these apps are connected in categories of similarity.

To sample top apps for each religion, we identified two keywords for each religion: Christian, Christianity; Islam, Muslim; Jewish, Judaism; Hindu, Hinduism; and Buddhist, Buddhism.

We queried these as keywords on App Annie, an app analytics site that uses market data to rank apps according to their popularity.

Bringing up the pages of top 100 ranking apps for each keyword for the United States marketplace on July 1st, 2015 (maintaining these settings for each query), we saved the results pages as HTML files.

We loaded each HTML page into a text editor to remove formatting.

Then we pasted the text into the DMI Harvester, which provided a CSV file.

We opened the CSV in Excel and deleted all rows except the 100 app links, identifiable by a URL beginning with https://www.appannie.com/apps/google-play/app/. We determined that the final portion of the URL was the unique page ID for each app in the Google Play store.

We appended the similar to URL base (https://play.google.com/store/apps/similar?id=) to each of these (e.g. https://play.google.com/store/apps/similar?id=com.calendar.hindu).

Opening the Import.io app, we clicked New -> Magic and pasted one of these appended URLs. This returned the similar to list of apps from the Google Play store along with their associated data. We saved these as CSV files to be organized into graph files. We repeated this manual copying/pasting/saving for each link.

Google Play Similar Apps Tool - Automated Method

At this point, we had determined the steps necessary to program a tool to automate many of these steps. Using the new Google Play Similar Apps Tool, we followed the procedure:

Carry out steps 1-5 in the semi-manual method in order to obtain the Google Play Store URLs for each app.

In the CSV with the app URLs, user the Replace function to isolate the app IDs (e.g. com.calendar.hindu).

Paste the list of app IDs in the Google Play Similar Apps tool (Figure 1).

Add a name for your result and press Get similar apps. This outputs both an HTML and CSV version of the data along with a Similarity network file.

Import the network file into Gephi for further analysis.

Figure 1. Step three in the automated procedure.

We imported each network into Gephi separately and analysed the individual app ecologies for each religion. We laid out the networks using Force Atlas 2 to identify clusters. Then we examined the node degree, indicating how many apps pointed to other similar apps, and we examined the modularity of each network, identifying which apps were most closely connected. Then we appended all graphs together in gephi to make an overall network, which we analysed by degree, modularity, and query type.

Findings

Judaism:

The Judaism/Jewish data set consists of roughly three main topic spaces structured by app clusters for religious texts, lifestyle, and media. The largest cluster features Jewish bible, prayer, and song apps. Closely related to this area is a cluster focused on studying the Torah. The second topic space is a lifestyle space that includes clusters for dating apps as well as kosher restaurants, wallpaper, and calendar apps. The final topic area on the left is dominated by apps for news, music, and other media outlets.

Buddhism:

The top and right of this app ecology is dominated by two clusters featuring Buddhist literature (quotes, manuals, songs, and stories). The left side of the network is defined by a pink cluster featuring Buddhist music and ringtone apps. Minor clusters within the network include apps for meditation, calendars, and specific mantras (Dhammapada, Om Mani Padme Hung, and Nīlakaṇṭha Dhāraṇī).

Hinduism:

The largest cluster in the Hinduism network (Figure __), appears in royal blue and was characterized by support tools, such as calendars, wallpapers, sayings, and phone features, such as a special caller ID feature and ringtones. The second largest clusters were prayers and books (bottom right yellow) and a cluster of horoscope, astrology, and wallpaper apps (top red). The Hinduism network had a fair-sized cluster of news-related apps, some of them specific to Hinduism while others were more mainstream, such as the BBC news app.

Christian:

3 Big Clusters (8+ central nodes):

Remarkable Ecology:Big cluster around Christian Music (yellow, right-bottom): music, songs, radio, Christian rap, etc. This cluster is also linked to smaller categories of Music Clusters (ringtones, etc) and spills over to other clusters, such as the Books Cluster (green, bottom-left) and the Kids Cluster (orange-ish, right)

Islam:

Conclusion

App ecologies are very much shaped by the nature of religious practices. As a whole, the ecologies show us a kind of technicity of religion, or the tools that are commonly used to perform a religion. For instance, the Islam/Muslim space contains many calendar apps, compasses, and prayer time apps to assist with Ramadan and daily religious rituals. While many of the religions share attributes like wallpapers or ringtones, they vary in their emphasis on prayer, religious study, music, mantras, and lifestyle choices like food or dating across religions.

Further Research

Compare app ecologies across platforms. For instance, how does Google Play compare to the iTunes App store?

In what other ways do apps fit into the rituals and textures of everyday life? What further categories can we explore aside from religion Examples: college, LGBT, business, etc.

User-oriented exploration - e.g. How does the app ecology generated by the store compare to the user-organized ecology?

How do users navigate the app ecology? Do they go with the app stores logic or do they resist it?

Presentation slides

Related literature

Eaton, Ben, Silvia Elaluf-Calderwood, Carsten Sørensen, and Youngjin Yoo. 2011. Dynamic Structures of Control and Generativity in Digital Ecosystem Service Innovation: The Cases of the Apple and Google Mobile App Stores. London School of Economics and Political Science. http://is2.lse.ac.uk/wp/pdf/wp183.pdf.